1135results about How to "Improve dynamic performance" patented technology

The invention discloses a battery monomer, a battery device and a power utilization device. Each battery monomer comprises a positive pole piece, a negative pole piece and an electrolyte; the lithium ion conductivity of the electrolyte is greater than or equal to 10 mS / cm; the negative electrode plate comprises a negative electrode current collector and a negative electrode film layer arranged on at least one side of the negative electrode current collector, the negative electrode film layer comprises a negative electrode active material, the negative electrode active material comprises a core part and a coating layer at least partially coating the surface of the core part, the core part comprises graphite, and the coating layer comprises graphite. In an R value cumulative distribution curve obtained by the negative electrode active material in a surface scanning mode of a laser microscopic confocal Raman spectrometer, an R value R50 with cumulative distribution of 50% is 0.15-0.50; in the obtained R values of the negative electrode active material, the number ratio of the R values smaller than or equal to 0.11 is smaller than or equal to 15%. The battery monomer provided by the invention has good dynamic performance and long cycle life.

The invention relates to the technical field of storage equipment management, in particular to an intelligent control method and system for storage equipment, and aims to solve the problems of task allocation, path optimization and equipment collaboration in a complex storage scene. According to the method, a storage equipment function model comprising an upper-layer frame model and a lower-layer equipment model is constructed, task allocation and path planning are optimized by using a neural network model in combination with task requirements, and a storage equipment control instruction is generated. In the task execution process, task priorities and path planning are adjusted in real time to adapt to dynamic environment changes, and it is ensured that tasks are completed efficiently. According to the method, a task distribution diagram and a path planning scheme are further optimized through a dynamic task diagram and a dynamic energy field, the problems of equipment congestion, too high energy consumption and task delay are effectively solved, the collaboration efficiency and the resource utilization rate of storage equipment are improved, and the method is suitable for various complex storage scenes.

The invention discloses a four-rotor unmanned aerial vehicle fault-tolerant formation control method with an anti-interference capability, and the method comprises the steps: building an unmanned aerial vehicle cluster system, and building a translation dynamics model, a rotation dynamics model, a motor dynamics model and an actuator fault model for each unmanned aerial vehicle; designing a nominal formation controller, and estimating and compensating a deviation fault of an actuator and external time-varying disturbance by combining a high-order sliding-mode observer to realize trajectory tracking control of each four-rotor unmanned aerial vehicle on a virtual navigator; a position ring and an attitude ring are decoupled, an attitude controller is designed for a nominal system, and a high-order sliding mode observer is combined to solve the influence of external time-varying disturbance on the attitude ring so as to realize attitude stability of each four-rotor unmanned aerial vehicle; the lift coefficient of each rotor is calculated based on a Newton correction method after the actuator has a fault to realize online fault diagnosis, and the rotating speed of each motor is calculated according to the control efficiency matrix after the fault to realize safe and reliable formation control of the quad-rotor unmanned aerial vehicle after the actuator has the fault. And the stability and the safety of the four-rotor unmanned cluster during flight are improved.

The invention relates to the technical field of information security, in particular to a cloud-based EMM encryption method and system, and the method comprises the following steps: collecting user login data and equipment use data based on mobile equipment operation information, recognizing the time and position information of user login and equipment use, calculating the risk scores of various behavior modes, and storing the risk scores of various behavior modes. And obtaining user behavior identification data. According to the method, the comprehensiveness and the dynamism of data security management are improved by collecting and analyzing the user login data and the equipment use data in real time, identifying unauthorized access and performing risk scoring on the mobile equipment, and encryption parameters are optimized by combining real-time monitoring on the user behavior pattern and the equipment performance and utilizing data sensitivity scoring; the data encryption efficiency and security are improved, the risk of data leakage is reduced by adjusting the updating frequency and parameters of the encryption key, the response speed to security threats is improved, the flexibility of enterprise data protection is enhanced, and the service continuity is maintained.

The invention relates to a lithium ion battery and an electric device. The lithium ion battery comprises: a negative pole piece, which comprises a negative current collector and a negative active coating located on the negative current collector, the negative active coating contains silicon carbon particles, a carbon material and a binder, the specific surface area of the silicon carbon particles is S m < 2 > / g, and the silicon carbon particles account for the mass fraction W < 1 >% of the negative active coating; the electrolyte comprises a lithium salt, a solvent and an additive, the additive comprises fluoroethylene carbonate, and the fluoroethylene carbonate accounts for W2% of the mass fraction of the electrolyte; wherein 1 < = S < = 15, 1 < = W1 < = 20, 1 < = W2 < = 30, and 1 < = S * W1 / W2 < = 10. According to the scheme provided by the invention, the stability of the electrode interface film can be improved, the expansion of the silicon negative electrode is inhibited, and the cycle performance and the service life of the battery are improved.

The invention discloses an EPSS-based vulnerability accessibility rating method, relates to the technical field of network security, and is used for solving the problem that vulnerability path analysis is not clear. According to the method, multi-modal data in threat intelligence is analyzed, a uniform vulnerability multi-dimensional feature vector is dynamically generated in combination with a feature quantization and time correction strategy, and the risk of the vulnerability in an actual scene is comprehensively analyzed in combination with network topology analysis and protection strategy evaluation and environment sensitivity score quantization; the vulnerability priority is dynamically adjusted through attack path simulation in combination with path weights and protection measures, the criticality of vulnerabilities in an attack chain is quantified, it is ensured that high-risk vulnerabilities in a critical path are processed preferentially, and a repair task optimization model under resource and time constraints is established based on the vulnerability priority and a repair dependency relationship. According to the method, the accuracy and the dynamism of vulnerability reachability rating are remarkably improved, and the efficiency of vulnerability management and the actual protection effect are improved.

The invention provides a high-rate and high-first-effect biomass hard carbon composite negative electrode material and a preparation method and application thereof, the hard carbon composite negative electrode material has a core-shell structure, the core-shell structure comprises a core, an inner shell and an outer shell, the core comprises biomass hard carbon containing P and graphite microcrystals, the inner shell comprises graphene, and the outer shell comprises a carbon nanotube. According to the invention, the surface of the biomass hard carbon is coated with the graphene layer, the carbon nanotubes grow on the surface of the graphene in situ, and transition metal synergistically induces the hard carbon to be arranged and grow along the graphene layer in a high-temperature carbonization process, so that the graphene coating layer is tightly coated, and the cycle performance of the material is improved; transition metal ions catalyze graphitization to generate a more regular and ordered graphite-like layer microcrystalline structure coating layer, so that the defects of graphene and carbon nanotubes are reduced, and the first coulombic efficiency is improved; in addition, the ion transmission capability is improved by phosphorus doping, the electron transmission capability is improved by graphite microcrystals generated by catalysis in hard carbon, and the rate capability is ensured by synergistic improvement of ion transmission and electron transmission.

The invention discloses an aero-engine control system and method based on self-adaptive specified interference cancellation, and belongs to the field of aero-engine control. A disturbance affine form nonlinear mathematical model of an aero-engine is obtained through system identification, a fixed-time disturbance observer is designed to estimate the lumped interference of the system in real time, and the disturbance of the aero-engine is estimated in real time; and a self-adaptive specified interference elimination composite controller is constructed based on a nonlinear backstepping method and a dynamic inverse method, so that accurate control on the rotating speed of the engine is realized. The system adjusts the control quantity in real time based on a backstepping method and a dynamic inverse method, and the controller adopts a non-smooth instruction filter and a self-adaptive dynamic weight distribution mechanism, so that the uncertainty of the system is effectively compensated. The method can effectively cope with uncertainty caused by system parameter perturbation, unmodeled dynamics and external load fluctuation, gives consideration to dynamic and static performance, has high control precision, good anti-interference capability and closed-loop stability, and is suitable for aeroengine rotating speed control under complex working conditions.

The invention discloses a power supply starting control circuit, a power supply starting control method and electronic equipment. The power supply starting control circuit comprises a first electric energy conversion circuit, a resonance circuit, a second electric energy conversion circuit and a main control circuit, the main control circuit is configured to obtain a resonance current signal and a power supply output signal in a second start-up stage, so that the resonance current signal is generated when the power supply output signal is not greater than the target reference voltage. Performing slope compensation on an adjustment output signal obtained by using a difference value between the power supply output signal and the target reference voltage by using the first slope compensation slope to obtain a first feedback adjustment signal, and generating a second control signal by using the first feedback adjustment signal and the resonant current signal; the target reference voltage is linearly increased in the second starting stage; the first electric energy conversion circuit receives the first control signal and the second control signal and adjusts the converted and output first alternating current signal by using the first control signal and the second control signal in sequence. By means of the mode, the power supply starting control circuit can effectively achieve smooth starting control.

The invention discloses a three-phase permanent magnet synchronous motor full-speed-domain driving control system and a control method thereof. The system is composed of a torque limiting module, a full-speed-domain control neural network module, a current control module, a coordinate transformation module-I, a coordinate transformation module-II, a coordinate inverse transformation module, an SVPWM module, a SiC MOSFET driving module, a full-speed-domain position rotating speed observation module, a weak magnetic feedback module and a three-phase permanent magnet synchronous motor. The control method is used for driving the control system. According to the method, accurate tracing of the optimal dq-axis reference current working point is realized based on deep learning, and accurate control of three operation modes of MTPA, field weakening control and MTPV is realized; an improved mobile vision field estimation algorithm is adopted, and the rotor position and the rotor rotating speed are accurately estimated within the full-speed domain range; the SiC MOSFET is used as an inverter switching tube, and a brand new drive circuit is designed to adapt to the operation condition of the electric vehicle.

The invention relates to a dynamic analysis optimization method for a high-speed stamping hybrid mechanism with a lubricating gap and considering an impact load. The dynamic analysis optimization method comprises the following steps: S1, defining structural parameters and design parameters; s2, establishing a lubrication gap motion model, a contact force model and an oil film bearing force model; s3, introducing a flexible beam unit model; s4, the relative motion state of the bearing and the shaft at the revolute pair element is judged; s5, establishing a kinetic equation; s6, solving the kinetic equation; s7, optimizing and improving the structural parameters of the mechanism; and S8, circulating the above process, and carrying out iterative solution until the kinetic analysis and parameter optimization are completed. The established rigid-flexible coupling kinetic equation containing the lubricating gap can more accurately predict the mechanism dynamic response characteristics of the high-speed stamping hybrid mechanism when the high-speed stamping hybrid mechanism is subjected to the impact load in actual work and operation, and the modeling method is suitable for dynamic response characteristic analysis and optimization design of high-speed stamping mechanisms of other configurations. The method has the advantages of wide applicability and the like.

The invention discloses a modeling method of a fractional order LC type three-phase inverter, and relates to the technical field of modeling and control of power electronic converters. On the basis of a traditional integer order LC type three-phase inverter, an integer order LC type filter in the inverter is replaced by a fractional order LC type filter, so that a new fractional order inverter topology is constructed. On the basis of the topology, mathematical models under a three-phase static abc coordinate system and a two-phase rotating dq coordinate system are constructed. Based on the mathematical model, a voltage and current double-closed-loop decoupling control strategy of the fractional order LC type three-phase inverter is deduced. In addition, a traditional virtual synchronous generator control link is replaced by an FOVSG control link, and the stability of the FOVSG control link is analyzed through a small signal model. According to the invention, dynamic decoupling can be effectively realized according to the order of the fractional order LC filter. In addition, an adjustable order is introduced in the FOVSG control link, and the performance of the inverter is improved under different control requirements.

The invention relates to the technical field of battery materials, in particular to a graphite negative electrode material and a preparation method and application thereof. The graphite negative electrode material comprises graphite particles, the average length La of the graphite particles in the alpha-axis direction of microcrystals is larger than or equal to 40 nm, the average thickness Lc of the graphite particles in the c-axis direction of the microcrystals is larger than or equal to 25 nm, and the interlayer spacing d002 ranges from 0.336 nm to 0.338 nm, and the number parameter of the microcrystals contained in each single graphite particle is defined as N = D503 / (La2 * Lc); d50 is the median particle size of the graphite particles, the unit is [mu] m, and the numerical value of N is more than 0 and less than or equal to 0.04. The graphite negative electrode material disclosed by the embodiment of the invention comprises the graphite particles with stable microcrystalline structure, large microcrystalline size and large interlayer spacing, so that the expansion and stress distribution uniformity of the negative electrode material in the circulation process is improved, the diffusion of ions in the graphite particles is facilitated, the consumption of active lithium is reduced, and the service life of the negative electrode material is prolonged. And the dynamic and super-long cycle stability of the graphite negative electrode material is improved.

The invention provides a thick electrode and a preparation method thereof, and a lithium battery, the thick electrode comprises a current collector and an active coating, the active coating comprises an active material, a conductive agent, a dispersant and a composite binder, the composite binder comprises a binder A and a binder B, the binder A comprises at least two of sodium carboxymethyl cellulose, a polyacrylic acid binder and an acrylonitrile multipolymer, and the binder B comprises at least one of polytetrafluoroethylene and butadiene styrene rubber. The thick electrode has the characteristics of stable structure, good conductivity and high ion transmission efficiency, and the cycling stability of the battery using the thick electrode can be improved.

The invention relates to the technical field of batteries, in particular to a battery. The battery comprises a positive plate and a negative plate; the negative plate comprises a negative current collector and a negative active material layer positioned on at least one side surface of the negative current collector; the negative electrode active material layer comprises a negative electrode active material, the negative electrode active material comprises graphite particles and silicon carbon particles, and the graphite particles comprise first graphite particles and second graphite particles; the particle size Dv50 of the first graphite particles is greater than the particle size Dv50 of the second graphite particles; the positive plate comprises a positive active substance, and the positive active substance comprises a substance with a chemical formula of Li Ni < x > Co < y > Mn < z > M < k > O < 2 >. The battery provided by the invention can give consideration to relatively high energy density, relatively low expansion rate and excellent cycle performance.

The invention discloses a switching loss optimization control method and system of an energy storage DC converter. Comprising the following steps: firstly, acquiring battery side voltage / current and bus side voltage / current of the energy storage direct current converter; calculating according to the battery side voltage and the bus side voltage to obtain the voltage ratio of the two sides of the energy storage direct current converter; then, control power is obtained through calculation according to the battery side voltage / current and the bus side voltage / current; then, determining the working mode of the dual-active bridge circuit by using the control power of the energy storage direct-current converter; and finally, according to the working mode of the dual-active bridge circuit, the actual power of the dual-active bridge circuit is adjusted, and the switching loss optimization of the energy storage DC converter is completed. When the battery side voltage, the bus side voltage and the load power of the circuit are changed, the control power of the controller can be continuously changed, smooth transition is realized among all working modes, the output signal and the power gain are basically linear, and the dynamic response speed can be improved.

The invention discloses a backflow power optimization control method and system for a dual-active bridge DC-DC converter, and the method comprises the steps: determining a transmission power range of the dual-active bridge DC-DC converter in each working mode based on a voltage conversion ratio, determining the working mode of the dual-active bridge DC-DC converter according to a real-time calculated transmission power per unit value, and carrying out the optimization control of the backflow power of the dual-active bridge DC-DC converter. And finally, inputting the current optimal phase shifting ratio combination into a PWM (Pulse Width Modulation) generator of the dual-active bridge DC-DC converter, generating a control pulse wave of a switch tube, controlling the on-off of the switch tube, and optimizing the backflow power of the dual-active bridge DC-DC converter in real time. According to the invention, the working mode of the dual-active bridge DC-DC converter can be determined in real time, power control is directly carried out on the dual-active bridge DC-DC converter, large backflow power generated in the working process of the dual-active bridge DC-DC converter is effectively reduced, the loss of a converter switch is reduced, and the response speed and the dynamic performance of a system are improved.

The invention discloses a current disturbance compensation control method, device and system for a duplex-winding induction motor, and the method comprises the steps: obtaining a DC bus voltage value of a control winding corresponding to the duplex-winding induction motor, carrying out the analysis and processing based on a feedback adjustment model, and giving a current given value of the control winding corresponding to the duplex-winding induction motor; obtaining current values of double windings corresponding to the double-winding induction motor, carrying out observation analysis processing based on a disturbance observation model, and giving a current disturbance observation value of a control winding; based on a feed-forward compensation control model, performing feed-forward compensation analysis processing on the current disturbance observation value and the current given value of the control winding, and giving a voltage given value of the control winding; the output of the duplex winding induction motor is adjusted based on the voltage given value and the current given value of the control winding. According to the invention, control winding current disturbance can be observed, disturbance compensation is realized through feedforward, and finally decoupling control of the control winding current and the power winding current is realized.

The invention provides an ultrahigh-nickel single-crystal positive electrode material and a preparation method and application thereof.The ultrahigh-nickel single-crystal positive electrode material comprises fluxing agent doping elements and high-valence doping elements, the fluxing agent doping elements comprise Zr, Ce, Sr, Y, La, Sn or Na, and the high-valence doping elements comprise Sb, W, Nb, Ta, Mo, Ti or P; the doping amount of the fluxing agent doping element is omega A, the doping amount of the high-valence doping element is omega B, and omega A and omega B meet the following relational expression: 0.5 < 0.746 * exp [-omega B / (0.891 * omega A)] + 0.556 < 1.0. Omega A and Omega B meet a specific relational expression, two doping elements are effectively promoted to play a role, a small-particle-size and uniformly-dispersed single crystal is formed, the material has high stability and safety of the single crystal, a Li < + > diffusion path can be shortened, dynamics can be improved, and the advantage of high capacity can be achieved.

The invention discloses a USV rotary column stabilization control system considering complex disturbance and motor dynamic characteristics, belongs to the field of motion control systems of ocean mobile observation platforms, and aims to improve the stability and control efficiency of USV navigation. The method comprises the following specific steps: firstly, establishing a rotary column stabilizer lift model, a USV nonlinear rolling model and a servo motor dynamic model; then designing a Backstepping controller based on a differential item disturbance observer, estimating and compensating disturbance caused by external and model uncertainty in real time, then adjusting expected control input in real time, and ensuring that the output rolling angle tracks the expected rolling angle. The MPC controller based on servo motor state feedback is designed, the state quantity of the motor is fed back to the controller for prediction and adjustment, the problems of response lag and output overload of the servo motor in complex sea conditions are effectively solved, rolling angle error minimization and effective control over energy consumption are further achieved, and the service life of the servo motor is prolonged. And the purpose of multi-objective optimization is achieved.

The invention discloses a control algorithm of a photovoltaic energy storage inverter system, which belongs to the technical field of photovoltaic energy storage, and comprises the steps of combining PPO deep reinforcement learning, dynamically optimizing a grid-connected control strategy of an inverter by adaptively adjusting a virtual inertia and a damping coefficient, and simultaneously compensating disturbance in the system in real time by utilizing LADRC. According to the method, the robustness and the stability of the system under the complex power grid working condition are ensured, the technical problem of improving the robustness, the dynamic response capability and the grid-connected control precision of the photovoltaic energy storage inverter system is solved, the flexibility of the system is improved, the dynamic performance of the system under the non-linear interference condition is improved, and the reliability of the system is improved. The stability and robustness of the system are maintained, and the reliability and stability of the whole grid-connected process are also significantly improved.

The invention relates to the technical field of grid-connected inverter control, and discloses a grid-connected inverter model predictive control method based on a neutral-point potential fluctuation control factor, in the process of controlling a grid-connected inverter by using model predictive control, firstly, an SVPWM method and the model predictive control method are combined, the design of an objective function is simplified, and the model predictive control factor is optimized; the optimal switch sequence can be selected only by calculating the midpoint potential deviation; secondly, neutral-point potential balance control is realized in spatial modulation, a large sector is further divided into a plurality of small sectors, the position of the small sector where a reference voltage vector is located is determined, a switch sequence is selected from the determined small sectors for traversal, the traversal frequency is reduced, and the calculation efficiency is improved; and finally, designing a midpoint potential control factor, and greatly reducing the content of high-amplitude common-mode voltage on the premise of ensuring the balance of the midpoint potential. Moreover, the overall control structure is clear and easy to implement, and the dynamic performance and the steady-state tracking performance of the controller are both improved.

The invention discloses a hard carbon negative electrode material for a sodium-ion battery as well as a preparation method and application of the hard carbon negative electrode material. The hard carbon negative electrode material for the sodium ion battery is a graphite microcrystal cross-linked hard carbon material, and the carbon layer spacing is 0.37 nm to 0.40 nm; the range of the Raman D / G (w) value is 1.1-1.6; and the compaction density of the 3T powder is 0.96 g / cm < 3 >-1.10 g / cm < 3 >. The hard carbon negative electrode material for the sodium ion battery has high capacity, high compaction, high magnification and high cycle performance; meanwhile, amorphous carbon is directionally etched through chemical reaction, and a second carbon source is compounded on the basis, so that the crosslinking degree between graphite microcrystals (a structural unit of hard carbon) is improved, open pores are further promoted to be converted into closed pores, sodium storage sites of the closed pores are increased, and the density and conductivity of the hard carbon material are improved; and the capacity, the compaction density, the multiplying power and the cycle performance are improved.

The invention provides a method and a device for realizing cross-network equipment authentication in a distributed soft bus, and belongs to the field of encrypted communication. The method comprises the following steps: in a local area network, equipment configures an authentication mode, a central node address and an authentication strategy of an authentication list according to different service scenes to realize authentication; for a cross-network scene, the leaf node realizes cross-network authentication through the proxy node, specifically, the leaf node and the proxy node in a local area network where the leaf node is located are authenticated; cross-network authentication is carried out among the proxy nodes in different local area networks through a Hichain module based on a distributed soft bus; after the authentication of the two levels is completed, trust is considered to be established between the leaf nodes; and cross-network communication is carried out among the leaf nodes through a key rate generated by one-time mask encryption. According to the scheme, the limitation that the existing distributed soft bus technology is only limited to equipment authentication in a local area network is broken through, and safety authentication between cross-network equipment is realized.

The invention discloses a permanent magnet synchronous motor high-performance prediction control method based on a sliding-mode observer, and the method comprises the steps: S1, collecting the position and mechanical angular velocity information of a rotor, collecting the three-phase voltage and current data of a permanent magnet synchronous motor, and converting the three-phase voltage and current data into the voltage and current of a motor stator under a two-phase rotating coordinate system; s2, constructing a speed ring sliding-mode observer, estimating electrical and mechanical parameter perturbation interference and load torque interference on line, designing a rotating speed ring deadbeat prediction controller, outputting reference current at the next moment, and setting the amplitude limit of the output reference current; s3, a current loop sliding mode observer is constructed, electrical parameter perturbation interference is estimated online, a current loop prediction controller is designed in combination with the dead-beat prediction control principle, and voltage at the next moment is output; and S4, carrying out amplitude limiting modulation on the output voltage, obtaining a voltage under a static coordinate system through Park inverse transformation according to the voltage after amplitude limiting modulation, and outputting a switching signal to a three-phase inverter by combining a two-level space vector modulation module to drive the permanent magnet synchronous motor to operate.

The invention relates to the technical field of batteries, in particular to a positive electrode material and a preparation method and application thereof. The positive electrode material comprises a core layer and a shell layer coating the surface of the core layer, the core layer comprises a high-nickel multi-metal oxide and a doping element Q, and the Q comprises at least one of Al, B, Nb, La, Sr, Sb and Mo; the shell layer comprises a nickel-containing multi-metal oxide and a doping element M, the element M comprises the element Q and a doping element D, and the doping element D is selected from at least one of B, Sb, Nb, W, Zr, Ta and Mo; the element Q is different from the element D; the element Q is uniformly distributed in the core layer and the shell layer; the doping element D is distributed in a radial concentration decreasing manner from the surface to the interior of the shell layer, and the interior of the positive electrode material is of a radial structure. The positive electrode material provided by the invention has low 003 crystal face grain size and high microstrain, can realize structure optimization and core-shell concentration difference maintenance at the same time, and improves the electrochemical performance of the positive electrode material.

The invention discloses a preparation method and application of an ammonium ion pre-embedded Cu-MOF derived CuHCF / MXene electrode material, and relates to the technical field of new energy nanometer materials. According to the preparation method, Cu-BTC is taken as a sacrificial template, ammonium ion pre-embedding and flaky MXene compounding are carried out, and synthesis is carried out under the condition of coprecipitation at room temperature. The preparation method provided by the invention is low in cost and simple in process, and the obtained electrode material is excellent in morphology and performance. When the prepared CuHCF / MXene composite electrode is applied to capacitive deionization, the characteristic of high NH4 < + > adsorption capacity is shown. According to the preparation method, hydrogen-bond interaction is formed between H atoms in NH4 < + > and N atoms in CuHCF, so that the NH4 < + > adsorption potential energy is reduced, the adsorption capacity is improved, and meanwhile, the defects that CuHCF is prone to agglomeration, poor in conductivity and the like are overcome through self-assembly of the CuHCF and MXene.

The invention relates to a district and county level power industry carbon emission prediction method based on power carbon traceability. The method comprises the following steps: carrying out user side load prediction in different areas and time periods; carrying out distributed power supply output prediction in different regions and different time periods; performing energy storage charging and discharging scheme prediction and source side carbon emission factor prediction; carrying out load flow calculation on each node in different regions and time periods; constructing a power matrix; measuring and calculating a single-time-point carbon emission index; and measuring and calculating the long-time scale carbon emission. According to the method, prediction data of user power utilization, clean energy power generation and energy storage charging and discharging are integrated, the carbon emission measurement and calculation requirements of different time periods and regions can be met, the applicability and flexibility of the model are enhanced, accurate prediction of the carbon emission in the whole power distribution network load storage link can be achieved, and the accuracy of carbon emission measurement and calculation is improved; the method particularly focuses on the influence of policy changes of an electric vehicle, a distributed power supply and the like on the carbon emission, so that the prediction result can reflect actual changes brought by the policy changes.

The invention relates to an inertial navigation / polarization compass / laser velocimeter integrated navigation method, which belongs to the technical field of inertial navigation / integrated navigation, and comprises the following steps: mounting and fixing an inertial navigation system, a polarization compass and a laser velocimeter on a carrier, and acquiring coordinate systems of sensors; establishing a polarization compass error equation and a laser velocimeter error equation by considering a course angle installation error, a pitch angle installation error and a scale error of the laser velocimeter; and deriving an inertial navigation / polarization compass / laser velocimeter combined system state equation based on the error equation, establishing a measurement equation by taking the difference between the speed calculated by inertial navigation and the speed of the laser velocimeter and the product of the polarization vector of the polarization compass and the sun vector as observed quantities, and carrying out estimation and feedback correction on the system state. The invention provides an inertial navigation / polarization compass / laser velocimeter combined navigation method in a satellite navigation denial environment, which realizes full-autonomous and high-precision directional positioning.

The invention relates to the field of data processing, in particular to an environment perception data processing method and system based on an intelligent helmet. The method comprises the following steps: acquiring a scene image in front of a user and multi-source environment real-time sensing data; performing scene attribute state analysis on the multi-source environment real-time sensing data, and constructing a real-time scene attribute state diagram; performing contrast dynamic balance adjustment on the scene image in front of the user, performing super-resolution fusion reconstruction, and constructing a super-resolution scene image; performing object visual identification on the super-resolution scene image, and performing object bounding box segmentation processing to obtain a plurality of accurate scene object bounding boxes; and carrying out optical flow motion change analysis on the plurality of accurate scene object bounding boxes, and carrying out space-time scene structure evolution analysis so as to obtain dynamic scene evolution characteristic data. According to the method, the data processing efficiency of the environment perception data is improved, and the environment perception data is visualized more visually.